<![CDATA[Information needs can arise because of a knowledge gap in a person with the necessary information needs, one of which is knowledge in the field of computers and informatics, especially related to terms in the computer field. Therefore we need a system that makes it easy for users to meet the information needs needed by building a digital dictionary application related to computer terms and informatics by utilizing the search engine features in it. Search activities are carried out daily to meet information needs. However, an error that is often unavoidable in performing a search is a typing error in the query. As a result, the information sought is not as expected. Based on this, we need a system that can identify typographical errors in the search text. So in this research, a website-based dictionary of computer and informatics terms will be developed by applying Peter Norvig's spelling corrector using the Python language with the flask framework. The implementation results show that Peter Norvig's spelling corrector method can be applied to computer and informatics term dictionary applications. This can be seen at the level of accuracy reaching 89% in correcting 180 word variations that contain typographical errors based on the highest probability of each possible word in the corpus. However, there is a lack of this spelling corrector method, it is still difficult to overcome typos in spelling abbreviations and typographical errors that exceed 1 letter]]>
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